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Exploring community is fundamental for uncovering the connections between structure and function of complex networks and for practical applications in many disciplines such as biology and sociology. In this paper, we propose a TTR-LDA-Community model which combines the Latent Dirichlet Allocation model (LDA) and the Girvan-Newman community detection… (More)

– This article investigates the dynamic features of social tagging vocabularies in Delicious, Flickr and YouTube from 2003 to 2008. Three algorithms are designed to study the macro and micro tag growth as well as dynamics of taggers' activities respectively. Moreover, we propose a Tagger Tag Resource LDA (TTR-LDA) model to explore the evolution of topics… (More)

The presence of social networks in complex systems has made networks and community structure a focal point of study in many domains. Previous studies have focused on the structural emergence and growth of communities and on the topics displayed within the network. However, few scholars have closely examined the relationship between the thematic and… (More)

This article investigates the dynamic features of social tagging vocabularies in Delicious, Flickr and YouTube from 2003 to 2008. It analyzes the evolution of the usage of the most popular tags in each of these three social networks. We find that for different tagging systems, the dynamic features reflect different cognitive processes. At the macro level,… (More)

Most researches about business components address the technical problems to draw the business process into structural model. But the basis of the "modeling" work is illustrating the real process precisely, which is not easy because of the difficulty to extract process information from the knowledge embedded in human experiences, especially when knowledge is… (More)

With the wide proliferation of text-based data on the Internet, there is a need for dealing with the information overload. The large amount of online user reviews may present an obstacle to developers who want to know users' feedback and potential customers who are interested in applications. Here we employ text analysis provided in SAS® Text Miner to… (More)